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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Displaying R spatial statistics on Google dynamic maps with web applications created by Rwui
|
|---|---|
| Published in |
International Journal of Health Geographics, September 2012
|
| DOI | 10.1186/1476-072x-11-41 |
| Pubmed ID | |
| Authors |
Richard Newton, Andrew Deonarine, Lorenz Wernisch |
| Abstract |
The R project includes a large variety of packages designed for spatial statistics. Google dynamic maps provide web based access to global maps and satellite imagery. We describe a method for displaying directly the spatial output from an R script on to a Google dynamic map. This is achieved by creating a Java based web application which runs the R script and then displays the results on the dynamic map. In order to make this method easy to implement by those unfamiliar with programming Java based web applications, we have added the method to the options available in the R Web User Interface (Rwui) application. Rwui is an established web application for creating web applications for running R scripts. A feature of Rwui is that all the code for the web application being created is generated automatically so that someone with no knowledge of web programming can make a fully functional web application for running an R script in a matter of minutes. Rwui can now be used to create web applications that will display the results from an R script on a Google dynamic map. Results may be displayed as discrete markers and/or as continuous overlays. In addition, users of the web application may select regions of interest on the dynamic map with mouse clicks and the coordinates of the region of interest will automatically be made available for use by the R script. This method of displaying R output on dynamic maps is designed to be of use in a number of areas. Firstly it allows statisticians, working in R and developing methods in spatial statistics, to easily visualise the results of applying their methods to real world data. Secondly, it allows researchers who are using R to study health geographics data, to display their results directly onto dynamic maps. Thirdly, by creating a web application for running an R script, a statistician can enable users entirely unfamiliar with R to run R coded statistical analyses of health geographics data. Fourthly, we envisage an educational role for such applications. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 4% |
| South Africa | 1 | 2% |
| Brazil | 1 | 2% |
| Mexico | 1 | 2% |
| Czechia | 1 | 2% |
| Unknown | 48 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 33% |
| Student > Ph. D. Student | 8 | 15% |
| Student > Doctoral Student | 5 | 9% |
| Student > Bachelor | 5 | 9% |
| Student > Master | 5 | 9% |
| Other | 9 | 17% |
| Unknown | 4 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 9 | 17% |
| Agricultural and Biological Sciences | 9 | 17% |
| Computer Science | 6 | 11% |
| Social Sciences | 5 | 9% |
| Medicine and Dentistry | 5 | 9% |
| Other | 12 | 22% |
| Unknown | 8 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 May 2013.
All research outputs
#14,914,476
of 25,374,647 outputs
Outputs from International Journal of Health Geographics
#374
of 654 outputs
Outputs of similar age
#108,919
of 190,204 outputs
Outputs of similar age from International Journal of Health Geographics
#10
of 15 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 654 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.7. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 190,204 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.